Warming-induced tipping points of Arctic and alpine shrub recruitment

Shrub recruitment, a key component of vegetation dynamics beyond forests, is a highly sensitive indicator of climate and environmental change. Warming-induced tipping points in Arctic and alpine treeless ecosystems are, however, little understood. Here, we compare two long-term recruitment datasets of 2,770 shrubs from coastal East Greenland and from the Tibetan Plateau against atmospheric circulation patterns between 1871 and 2010 Common Era. Increasing rates of shrub recruitment since 1871 reached critical tipping points in the 1930s and 1960s on the Tibetan Plateau and in East Greenland, respectively. A recent decline in shrub recruitment in both datasets was likely related to warmer and drier climates, with a stronger May to July El Niño Southern Oscillation over the Tibetan Plateau and a stronger June to July Atlantic Multidecadal Oscillation over Greenland. Exceeding the thermal optimum of shrub recruitment, the recent warming trend may cause soil moisture deficit. Our findings suggest that changes in atmospheric circulation explain regional climate dynamics and associated response patterns in Arctic and alpine shrub communities, knowledge that should be considered to protect vulnerable high-elevation and high-latitude ecosystems from the cascading effects of anthropogenic warming.

The Ittoqqortoormiit site is characterized by a tundra climate and has a short and warm growing season (June to August) and a mean annual temperature of −7.8 °C, with dark winter conditions lasting for more than seven months (Fig. 1). According to the gridded Climate

Shrub recruitment data
To examine long-term changes in shrub recruitment across tundra and alpine regions, we Lastly, shrub recruitment data were truncated in 1871, because the time coverage of available atmospheric circulation pattern records only dates back that far.

Climate data
The Arctic Oscillation (AO) is a natural climatic circulation pattern in high latitudes that emerges from sea level pressure anomalies at the 1000-hPa height (5) Specifically, there is an inverse relationship between ENSO and the Indian summer monsoon, which affects the growing season rainfall on the Tibetan Plateau (9). We used the monthly climate time-series of AO from the 20th century reanalysis (10), unsmoothed AMO and El Niño 4 (averaged sea surface temperature from the region of 5° S-5° N and 160° E-150° W, series available at https://psl.noaa.gov/gcos_wgsp/Timeseries/). The time span of these records ranges from 1871 to 2010.
Monthly CRU data of mean temperatures and total precipitation were obtained for the Ittoqqortoormiit site (0.5° resolution, period 1901-2010). We also obtained monthly CRU 4 mean temperatures and APHRODITE 0.25°-gridded total precipitation (4) (period 1951-2010) of the four study sites on the Tibetan Plateau. The average or summed series of temperature and precipitation data, respectively, were then used for analyses. Finally, we extracted long-term 5°-gridded temperature (11) (HadCRUT4, period 1850-2020) for Ittoqqortoormiit and the Tibetan Plateau and snow accumulation data in the Tibetan Plateau Dasuopu glacier (12) (i.e., a precipitation proxy) for our analyses.

Data analyses
Shrub recruitment may lag behind climate variability by several years (1), as shrubs need considerable time for seed maturation and seedling establishment. In this study, climate data (AO, AMO and gridded CRU data) and z-scores of annually shrub recruitment at the Ittoqqortoormiit site were, therefore, transformed into lower frequency (10-year moving averages) time series to reduce the impact of lagged climate-recruitment effects. For the Tibetan Plateau, the climate data were first transformed into 10-year moving average series to investigate the relationships between the ENSO and gridded temperature and precipitation.
Moreover, decadal gridded climate data and El Niño 4 were computed to detect their relationships with recruitment dynamics. For both study regions, we also calculated decadal time series of recruitment, climate series including mean temperature, precipitation, and snow accumulation data in Dasuopu for moving window Pearson correlation analyses. Each recruitment series was divided into two time series according to their peaks (tipping points).
Linear regressions were then applied to explore the relationships between large-spatial climate circulations and recruitment series by using the above 10-year moving average or 5 decadal resolved series. To test whether such relationships persist, we examined the relationships between the detrended recruitments series and climate circulations. We removed the year-related trend from those recruitment and climate series by extracting or dividing by the values calculated from linear regressions with the year as the only independent variable.
Recruitment series were also divided into two segments for the detrending process. To detect how atmospheric circulation patterns related to shrub recruitment declines, linear regressions were firstly used to evaluate the impacts of atmospheric circulations on the regional climate at the study sites. We then repeated the same approach to analyze the relationships between regional climate variability and recruitment. A 60-year moving window Pearson correlation analysis was used to detect whether the relationships between recruitment and its main limiting climate factors changed after reaching tipping points at each site.